On 5 November 1997, 1200Z the following small changes in the global
analysis/forecast system were implemented:

1. New observation errors in SSI analysis

2. Changes in assimilation of TOVS radiances

3. Inclusion of several additional data sources

4. Elimination of spurious "valley snow"

5. Soil moisture nudging toward climatology

6. Conservation of dry mass

7. Model structural changes

8. Changes in some GRIB output files

**(some of the ouput changes have been delayed see appendix)

2. CHANGES TO THE ANALYSIS SYSTEM

2.1 New observation errors in SSI analysis (W.-S. Wu)

In data assimilation, the weights given to the data are derived from the inverse of
the observation error covariance, while the weights for the fit to the first guess are
determined by the inverse of the background error covariance. Since the
observation errors include both the errors from the observations themselves and
errors of representativeness as well, their magnitudes are larger than what is
needed to account for just instrument and measurement errors.
The statistics of the current operational data assimilation system
at NCEP indicate that for some quantities the first guess fit to the data is better than
the observational error used in the SSI analysis. Since the guess fit includes not
only the observation error but also the model error, then the observation errors are
overestimated. With the guess fit to the data as guidance, we adjusted the
observational error mainly according to Stoffelen, et al., 1996. As an example, the
new temperature errors for rawindsondes and dropsondes are shown in Fig. 1 .

The modified error table was tested in the full resolution (T126) parallel run in
April, 1996 for over a month. The mean day 5 anomaly correlations for forecasts
of 500-hPa geopotential for each are given in Table 1. "MRF" is the operational
model, "X" is the experiment. An improvement of about .015 is found in both
hemispheres. The temporal standard deviations are smaller for the experiment,
indicating that the scores are more consistent from case to case.

The main changes in the direct use of the TOVS radiances in the SSI analysis
system are (a) the exclusion of HIRS channels 16, 18 , and 19, and (b) the
elimination of NESDIS temperature retrievals above the top of the
model in favor of using model layers to represent the whole profile. These
changes have been found to decrease the temperature bias found between 100 and
300 hPa and to improve the fit of the 6-hour guess to the data. Results from a
month of parallel testing at T126 in August, 1996 show very little impact on the
500-hPa geopotential anomaly correlations for 5-day forecasts given in Table 2.

For a number of years users of the MRF have complained of persistent fixed
For a number of years, users of the MRF have complained of persistent fixed
( Fig. 2 , left side). The cause has been traced to the use of a time-saving
approximation for the elimination of errors in the conversion of horizontal
diffusion on the model's sigma surfaces to diffusion on pressure surfaces. The
approximation to the correction term used in the diffusion equation is

where Ps is the surface pressure and q-bar is the global average of q, the specific
humidity. It is the vertical derivative of the global average of specific humidity that
creates spurious moisture sources in valleys in arctic air, moisture deficits over
high terrain, and spurious gradients. The prominent wave patterns are
a result of the inability of a spectral model to handle such intense
gradients properly. The current problem has been greatly reduced by the elimination
of this correction ( Fig 2 right side) but a permanent solution
will require the development of a better parameterization of horizontal diffusion.

3.2 Soil moisture nudging toward climatology (S. Saha)

Since there are no widespread routine soil moisture measurements, the GDAS
system calculates updates for soil moisture from the model forecast.
Consequently, deficiencies in model precipitation and runoff forecasts may cause
the soil moisture to drift far from reality and, in the process, cause drifts in other
model fields as well. In order to prevent this, we are implementing a relaxation
scheme to nudge the model soil moisture to the climatological values. The
relaxation time of 60 days is chosen so that we can allow a within-season response
of the soil to seasons with either drought or abundant rainfall, while keeping the
longer-term soil moisture bounded. The climatology is a recent product of the
Climate Prediction Center of NCEP that makes use of both observed precipitation
and surface air temperature climatology.

Extended-range operational model runs (up to twenty years) have shown that
while the model soil moisture does not lead to disasters (i.e., permanent desert or
swamp), there can be significant departures from climatology that do not
correspond to observed anomalies in precipitation. This change should prevent
such departures from happening to operational products.

3.3. Conservation of dry mass (S. Saha)

The MRF does not exactly conserve mass - neither dry air mass nor water vapor.
For short- and medium-range forecasts this has not been a problem because the
loss is on the order of several mb/year. However it needs to be corrected for
seasonal forecasts or longer. From physical considerations, only the global mean dry
mass should be
conserved. The fix applied is thus to to reset the global mean dry pressure to its
initial value. Note that the global mean total pressure can still vary in response to
the changing atmospheric water load.

The global spectral model can now be run in a single step and can now invoke
surface cycling (to update climatology). These restructurings allow model scripts
to be more flexible, especially for longer forecasts and climate runs; they change model
architecture only and do not affect the model results.

4. PARALLEL TESTING AND EVALUATION (P.Caplan)

The changes that are to be implemented were each tested separately for various
periods of time at T62 resolution, and then together for over three months at T126
in parallel with the operational MRF. These parallel runs were not only evaluated
objectively with standard statistical measures, but also subjectively by the Medium
Range Desk and the International Desk.

4.1 Objective scores against analyses

The results of testing the above changes in the parallel system
for three continuous months (March through May of 1997)
are given in the next series of figures. Fig. 3a and Fig. 3b
show anomaly correlations for 500 hPa geopotential height forecasts for latitudes 20-80 degrees in each
hemisphere, with each model verified against its own analysis. The new system (labeled X) scores
slightly higher than the MRF system at all forecast lengths and for all zonal wavelengths.
Fig 4 shows
just the 5-day forecasts from the above data, plotted as a scatter diagram of the new system (X)
against the operational(MRF). The amount of scatter is much greater in the Southern
Hemisphere, as usual. In the tropics (20S-20N), the models are also close, with the operational
MRF better at 850 hPa and the X better at 200 hPa, as can be seen both from the anomaly
correlations of the wind components ( Fig. 5 ) and the rms vector errors ( Fig. 6 ).

4.2 Objective scores against observations - wind and temperature

The 72-h wind and temperature forecasts from the two systems were evaluated
also against observations from near the surface up to 100 hPa over the above
three-month period, plus June. Against rawinsondes in the Northern Hemisphere
and in the tropics the two systems performed almost identically, while in the
Southern Hemisphere a slight improvement (up to 3%) was noted in the rms vector
errors in the middle and upper troposphere ( Fig. 7 ). For temperature errors, the
results were similar: noticeable difference only in the Southern Hemisphere, where
the errors were reduced slightly at most levels but more substantially near 200 mb,
where a negative bias was reduced by some 25%. Verifications against satellite
wind observations and aircraft observations also showed little effect outside the
Southern Hemisphere, where small improvements were noted. The fit of the 6-h
first guess to rawinsonde observations is shown in the same form in Fig. 8 . The
overall pattern is quite similar to that found at 72 h.

4.3 Objective scores against observations - precipitation

For 1-day and 2-day precipitation forecasts over the continental United States
the performance of the new system was quite similar to that of the old. Fig. 9
shows equitable threat scores and biases averaged for March through June. (The
threat scores with the new system were slightly worse in March and April, and
slightly better in May and June).

4.4 Results of subjective evaluations

As is the current procedure for implementations, parallel forecasts from the new
system were examined side-by-side with those from the operational system at the
daily map discussions in the Meteorological Operations Division at NCEP. Over
North America there were noticeable but non-systematic differences from day to
day, but no clear winner in skill. In the tropics, where both systems are prone to
generating spurious shallow disturbances along the ITCZ, the new model at times
seemed somewhat noisier than the operational. Elsewhere in the tropics there was
little difference.

5. CHANGES IN OUTPUT FILES

The output GRIB files will also contain a few slight changes. For the AVN runs only, the 10 new levels will be added to the 0-, 12-, 24-, and 36-h forecast files so that the minimum vertical resolution will be 50 hPa.
In addition, three fields describing convective clouds will be added -
coverage, level of the tops and level of the bottoms.
There will also be some changes in labeling to clarify the contents of several
of the existing GRIB files (see appendix).

6. SUMMARY

Minor changes have been made to the GDAS/MRF analysis and forecast system
Potentially the most significant of these is the reduction of the errors assigned to
the observations so that the analysis can draw more closely to the data. In the
forecast model the nudging of the soil moisture toward climatology should insure
against
excessive model drifts where precipitation is poorly forecast. The change in
moisture diffusion should largely eliminate spurious wavelike paterns of snow in
arctic air masses.

These changes led to a slight improvement in anomaly correlation scores against
analyses for 500-hPa geopotential in the Southern Hemisphere. In the tropics, the
new model seemed slightly better at 200 hPa and slightly worse at 850 hPa against
analyses, but there was very little effect against observations. The effects of the
changes on 2-day precipitation forecasts over the U.S. were slightly negative but
small overall.

7. LOOKING AHEAD

Over the coming year, many development projects for the global data
assimilation
and forecast system will be coming to fruition. It is anticipated that a major portion of these
projects should produce substantial improvements in precipitation
forecasts. The development strategy is focused in four major areas:

First the number of data sources available to the data assimilation system
will increase when GOES sounder and DMSP T/T2 radiances are incorporated.
Later, use of NOAA-K AMSU-A/B data will be developed and tested. All of
these data sources are particularly important for moisture analysis to help
maximize the amount of data available for moisture analysisis, which is a prerequisite for other developments.

One of the most serious (and difficult) problems in the current data assimilation
system is the moisture (water vapor, clouds and precipitation) analysis. Over
the next year, all satellite data available to the analysis will be used more
effectively with improved calculation of radiative transfer for those instrument channels
most sensitive to atmospheric moisture. Other analysis upgrades should also
produce an improved moisture analysis. A major research effort to use
satellite-based
cloud and precipitation information in the analysis will be initiated, which
should improve the moisture/dynamics coupling and provide considerably
improved
precipitation forecasts.

In addition to the improvement of initial conditions for the forecast models, improved
precipitation products using the global ensembles will be produced. Probabilistic
quantitative precipitation forecasts (PQPFs) that have been corrected for model
bias will be introduced. This will be done in conjunction with ensemble techniques,
thus implementing a powerful methodology for providing
more information to the forecaster on 3-5 day forecast rainfall and for correcting
persistent model biases.

Last, upgrades to model physics should improve precipitation scores. It is
believed that a major cause of the large bias is the interaction of the over-land
boundary layer with the surface, particularly for evaporation during nighttime.
Current tests of surface physics upgrades and modifications to the model vertical
diffusion, along with increased resolution in the data assimilation, are not
complete at this time but are very encouraging. A scheme to include prognostic
cloud water in the global forecast model will continue to be developed and
tested.

In summary, major development will occur on the primary ingredients for QPFs:
improved moisture analysis, precipitation products geared to maximum forecaster
usage, and changes to model physics.

NOTE!!! The changes in the number of levels in the AVN output were
temporarily withdrawn at the request of some users. They will appear
at a future date.

(1) Both the pressure GRIB file and the surface flux file have the following
changes and additions:

(a) The maximum and minimum temperature fields now reflect the time period
over which they are valid. Previously, they were imprecisely labelled
instantaneous.
For instance, the PDS for the 24-hour MRF forecast used to be:

(2) For the AVN only, and only at forecast hours 00, 12, 24, and 36,
extra pressure levels are added to the pressure GRIB file so that
the minimum resolution is 50 mb.
Thus the new fields for these few files are:

Fig. 1 Rms temperature errors as a function of pressure level for the guess for
rawinsondes (open rectangles) and dropsondes (open triangles) and for the
rawinsonde observations in the operational system (filled rectangles) and the new
system (filled triangles)

Fig. 2 Precipitation for the first 24 hours of the forecasts over Antarctica averaged
over the month of August, 1996 for the operational system (left) and the new
system (right)

Fig. 3a Anomaly correlations for 500-hPa geopotential, forecast days 0-5,
latitudes 20-80 N, operational system (MRF, solid lines) versus
new system (X, dashed lines). The results are averaged for forecasts verifying
over the period 2 March through 1 June 1997 with 92 cases for the MRF and 89
cases for the X. Four zonal wave number groups are shown. Each model is verified
against its own analysis.

Fig. 4 Anomaly correlations for 5-day forecasts of 500-hPa geopotential for the regions and period shown in Fig. 3 for operational (MRF) vs. new system (X). N. Hem scores given by (x) and S. Hem by (o).
>

Fig. 5 Anomaly correlations for the v-component of winds in the tropics (20S-20N)
for forecast days 0-5 at the 850- and 200-hPa levels, operational model (solid lines)
vs new system (dashed lines), forecasts verifying 2 Mar through 1 Jun 1997.

Fig. 7 Four-month average of vertical profiles of temperature errors (first column)
and wind errors (second column) for 3-day forecasts verified against rawinsonde
observations. The left-hand pair of each set of four curves is the bias, the
right-hand pair is rms error, for operational (solid) and new system (dashed). The
third column shows number of observations in the average. Different regions
are shown in different rows, N Hem. extratropics in the top row, then S. Hem.
extratropics, then tropics, then polar regions.